#!/usr/bin/env python3 """ Generate precomputed 8x8 correlation previews as JSON for the preview split. Usage: # From a JSONL manifest listing parcellation/subject/corr_path python scripts/make_preview.py --manifest manifests/preview.jsonl --size 8 Notes: - Attempts to load correlation .mat using scipy.io.loadmat, falling back to mat73 if needed. - Variable name fallbacks: correlation_matrix | corr | A - Writes files under preview/____corr8x8.json """ import argparse import json import os from pathlib import Path from typing import Dict, Optional def try_import(): try: import scipy.io as sio # type: ignore except Exception: sio = None try: import mat73 # type: ignore except Exception: mat73 = None return sio, mat73 def load_mat(path: Path) -> Optional[Dict]: sio, mat73 = try_import() if sio is not None: try: return sio.loadmat(str(path), squeeze_me=True, simplify_cells=True) # type: ignore[arg-type] except Exception: pass if mat73 is not None: try: return mat73.loadmat(str(path)) # type: ignore[attr-defined] except Exception: pass return None def top_left_8x8(arr, size=8): import numpy as np a = np.asarray(arr) if a.ndim < 2: return None n = min(size, a.shape[-1]) return a[:n, :n].astype("float32").tolist() def main(): ap = argparse.ArgumentParser() ap.add_argument("--manifest", type=Path, required=True) ap.add_argument("--size", type=int, default=8) args = ap.parse_args() repo = Path(__file__).resolve().parents[1] out_dir = repo / "preview" out_dir.mkdir(parents=True, exist_ok=True) with args.manifest.open("r", encoding="utf-8") as f: rows = [json.loads(line) for line in f if line.strip()] wrote = 0 for r in rows: parc = r.get("parcellation") subject = r.get("subject") corr_path = r.get("corr_path") if not (parc and subject and corr_path): continue dst = out_dir / f"{parc}__{subject}__corr8x8.json" if dst.exists(): continue src = repo / corr_path if not src.exists(): print("skip missing:", src) continue data = load_mat(src) if not isinstance(data, dict): print("cannot load .mat (no scipy/mat73?)", src) continue for k in ("correlation_matrix", "corr", "A"): if k in data: sl = top_left_8x8(data[k], size=args.size) if sl is not None: with dst.open("w", encoding="utf-8") as g: json.dump(sl, g) wrote += 1 break print(f"Wrote {wrote} preview tiles to {out_dir}") if __name__ == "__main__": main()